Optimal trade-off filters for compressed Raman classification and spectrum reconstruction - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Journal of the Optical Society of America. A Optics, Image Science, and Vision Année : 2023

Optimal trade-off filters for compressed Raman classification and spectrum reconstruction

Résumé

Compressed Raman spectroscopy is a promising technique for fast chemical analysis. In particular, classification between species with known spectra can be performed with measures acquired through a few binary filters. Moreover, it is possible to reconstruct spectra by using enough filters. As classification and reconstruction are competing, designing filters allowing one to perform both tasks is challenging. To tackle this problem, we propose to build optimal trade-off filters, i.e., filters so that there exist no filters achieving better performance in both classification and reconstruction. With this approach, users get an overview of reachable performance and can choose the trade-off most fitting their application.
Fichier sous embargo
Fichier sous embargo
0 6 14
Année Mois Jours
Avant la publication
dimanche 10 novembre 2024
Fichier sous embargo
dimanche 10 novembre 2024
Connectez-vous pour demander l'accès au fichier

Dates et versions

hal-04279295 , version 1 (10-11-2023)

Identifiants

Citer

Timothée Justel, Frédéric Galland, Antoine Roueff. Optimal trade-off filters for compressed Raman classification and spectrum reconstruction. Journal of the Optical Society of America. A Optics, Image Science, and Vision, 2023, 40 (6), pp.1058. ⟨10.1364/JOSAA.479569⟩. ⟨hal-04279295⟩
10 Consultations
2 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More